The study of precipitating events is central to the understanding of geriatric syndromes such as delirium, falls, and functional decline. As longitudinal studies are increasingly used to identify and understand the mechanism of precipitating events, several methodological issues must be addressed. First, there is the potential for data collected at the time of an observed precipitating event to add important information to data collected at regularly scheduled fixed time intervals. However, it is uncertain how to best model these "triggered" data without introducing bias and whether these data provide additional explanatory information. Second, the study of precipitating events typically assumes a one-way relationship between the event and the outcome of interest. However, the possibility of a feedback loop exists, such that the outcome may be a risk factor for the precipitating event which may lead to a future outcome and so on. These methodological issues are also highly relevant to the study of patients' treatment preferences. This proposal will make use of an existing longitudinal database examining the relationship between changes in older persons' functional status (the precipitating event) and changes in their treatment preferences (the outcome) to examine these issues. The results of this study will help researchers better design (and analyze and interpret data from) future longitudinal studies examining the relationship of precipitating events to a wide variety of multifactorial geriatric syndromes.